docstr: Saves the Estimator state (including model and optimizer) to the provided model_path.
  
  :param model_path: (str) Path to save the model.
  :return:
docstr_tok: ["Saves","the","Estimator","state","(","including","model","and","optimizer",")","to","the","provided","model_path",".",":","param","model_path",":","(","str",")","Path","to","save","the","model",".",":","return",":"]
code: def save(self, model_path: str) -> str:
      """
      Saves the Estimator state (including model and optimizer) to the provided model_path.
  
      :param model_path: (str) Path to save the model.
      :return:
      """
      state_dict = self.get_state_dict()
      torch.save(state_dict, model_path)
      return model_path
  
imports: from bigdl.orca.learn.ray_estimator import BaseEstimator
  from bigdl.orca.ray import OrcaRayContext
  from bigdl.orca.data.file import enable_multi_fs_save, enable_multi_fs_load
  import io
  import torch
  import ray
  from ray.exceptions import RayActorError
  from abc import abstractmethod, ABCMeta
  from bigdl.orca.learn.pytorch.utils import find_free_port, check_for_failure
  from bigdl.orca.learn.utils import get_driver_node_ip
  from bigdl.dllib.utils.log4Error import invalidInputError, logging
  from typing import Dict
label_desc: Use image node_id 10 for calling the BaseRayEstimator obj's underlying member method code with example usage: obj.save(model_path) and returns: model_path